Learning
Deep reinforcement learning optimizes distributed manufacturing scheduling
A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their...
Machine learning method improves accuracy of inverse protein folding for drug design
Mask-prior-guided denoising diffusion (MapDiff) for inverse protein folding. Credit: Nature Machine Intelligence (2025). DOI: 10.1038/s42256-025-01042-6 An AI approach developed by...
HAPIR: a refined Hallmark gene set-based machine learning approach for predicting immunotherapy response in cancer patients
Overview of HAPIRHAPIR is a machine learning model used for predicting response to ICIs. The HAPIR workflow mainly consists of...
Combining technology, education, and human connection to improve online learning | MIT News
MIT Morningside Academy for Design (MAD) Fellow Caitlin Morris is an architect, artist, researcher, and educator who has studied psychology and used...
HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities
AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional Federated Learning (FL) supports...
